1. Field
Embodiments relate to a method and apparatus to generate an object descriptor using curvature gabor filters.
2. Description of the Related Art
The importance of security using face recognition is gradually increasing due to the recent prevalence of terrorism and information theft. Establishing a biometric recognition solution to prevent terrorism is interesting. A representative effective method to counteract terrorism is to reinforce border security and identity verification. The international Civil Aviation Organization (ICAO) has recommended that biometric recognition information be used by a mechanical travel document reader. The Enhanced Border Safety and Visa Entry Reform Act of the U.S. provides for an enhanced introduction level of biometric identifiers and associated software and mandates the use of biometric recognition information in travel documents, passports, and U.S. visas. Biometric passports have been adopted by several nations, such as some European countries, the United States, and Japan. In addition, a new type of biometric passport incorporating a chip in which biometric information of a user is stored has ever been used.
Many agencies, companies, and other types of organizations demand that their employees or visitors use admission cards for identifying individuals today. Accordingly, each employee or visitor may need to always carry a key card or a key pad for use with a card reader when he or she stays in a designated admission allowed area.
However, if the employee or visitor losses or is robbed of the key card or the key pad, serious security problems, such as invasion of an unauthenticated person into a restricted area, may occur. To prevent the security problem, biometric recognition systems to automatically recognize and verify personal identities using human biometric information or behavior characteristics have been developed. These biometric recognition systems have been used in banks, airports, and other high-security facilities, and more simplified and highly reliable biometric recognition systems have also been studied.
Personal features used by the biometric recognition systems include fingerprints, face shape, handprints, hand shape, thermal images, voice, signature, venous shape, typing keystroke dynamics, retina, iris, etc. Face recognition is the most frequently used personal identification technique to verify a personal identify from one or more faces present in a still image or a moving image using a given facial database. Facial image data may greatly vary depending on poses or illumination and therefore, it may be difficult to classify various pieces of pose data of the same person into the same class.
Although various image processing methods to reduce errors in face recognition have been recommended, these methods may result in errors caused by assumption of linear distribution and assumption of Gaussian distribution when attempting to recognize a face.
In particular, a gabor wavelet filter, which has been used in face recognition, is suitable to capture various changes, such as expression change and illumination change in a facial image, but may necessitate complex calculation processes when face recognition is performed using gabor wavelet features. Parameters of the gabor wavelet filter are restrictive. The use of the gabor wavelet filter having these restrictive characteristics may increase occurrence probability of errors in face recognition and deteriorate a recognition rate in face recognition. In particular, when expression change and illumination change in a facial image are significant, the recognition rate may be further deteriorated.